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Adapting End-to-End Neural Speaker Verification to New Languages and Recording Conditions with Adversarial Training
In this article we propose a novel approach for adapting speaker embeddings to new domains based on adversarial training of neural networks.
Generative Adversarial Speaker Embedding Networks for Domain Robust End-to-End Speaker Verification
Furthermore, we are able to significantly boost verification performance by averaging our different GAN models at the score level, achieving a relative improvement of 7. 2% over the baseline.
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